A Technical Note

Some of you may want to bypass this post, but in the interests of full disclosure:

I’ve made a couple of improvements to the regression model that underlies the analysis. The first adjustment is to weight the regression based on the depth of polling data that we have in a given state. Without this weighting, the regression would treat a state like Wyoming, where we have just one poll, as having as much influence over the model as a state like Pennsylvania, where we are already approaching a dozen. Among other things, this should allow the model to “read-and-react” more quickly to new polling data.

The second improvement is to consider a couple of new variables in the analysis: the percentage of the 2004 electorate that identified themselves as Democrat, Independent, and Republican in 2004, according to CNN exit poll data. Obama does comparatively worse in states where a larger share of John Kerry’s vote came from self-reported Democrats, and better where more of his vote came from Republicans and Independents. This is consistent with a finding from the recent Pew Poll, which shows Obama losing more self-identified Democrats to McCain than Clinton does, but getting a larger fraction of the vote from Republicans and Independents. This tends to give the model more confidence in Obama’s polling lead in a state like New Hampshire, which has a huge number (44% of the electorate) of self-reported Independents, while harming him in a state like West Virginia, where just 18% of the electorate identify as Independent (but 50% identify as Democrat).

The overall effect of these adjustments is to slightly hurt Obama’s win percentage, as he loses a few percentage points in industrial states like Pennsylvania that have relatively few independents (20% Independent, 41% Democrat in 2004). Clinton’s numbers have moved up a tiny bit.

To get even more technical, the way the regression model is programmed is to consider eight potential variables: